The present disclosure relates generally to systems and methods for medical and security imaging and, in particular, to systems and methods for producing high-resolution tomographic images.
In past years, there have been many advances in the physics of medical tomographic imaging systems, one of the most notable being the advent of multi-detector row helical systems. Generally, the resolution of conventional tomographic systems has been driven by detector size and angular sampling. Historically, these quantities have been constrained to a regular polar coordinate grid sampling in Radon space, whereby higher resolution systems have required smaller, more expensive, detector elements and increasingly dense data acquisition systems, raising the cost and complexity for enhancing imaging capabilities.
Some techniques have been developed to improve sampling density, and thus achieve a higher resolution for existing CT systems. For example, in the quarter-detector off-set approach, the detector bank, which ordinarily is symmetric with respect to the line joining the x-ray source and the center of rotation, is offset the left or right, thereby providing extra additional views used to obtain supplementary information about the imaged object. However, for cone-beam scans and for spiral scans data redundancy from this approach is not really available since opposing rays do not coincide, but rather differ by tilt-angle with rotation and longitudinal position. Further, the quarter shift does not improve the sampling in the detector row direction, or longitudinal direction. Similarly, the flying focal spot (FFS) technique aims to increase sampling density by using periodic deflections of the focal spot in the in the radial direction and longitudinal direction. This approach can be used to double the sampling density in both directions regardless of the cone-angle and the spiral trajectory.
In addition to CT systems, a few approaches have been previously employed to achieve enhanced resolution in Positron Emission Tomography (PET) imaging. Some examples include using a combination of multiple low resolution images, dichotomic ring sampling, bed wobbling, and blurring kernel estimation on sinogram, to name a few. However, fundamental limits of spatial resolution in PET are related not only to the physical size of the detector or the non-collinearity of the detector geometry, but also to positron range modeling, detector cross-talk, and so forth. Approaches to overcome these limitations are still under investigation. Likewise, non-uniform sampling schemes based on general k-space trajectory studies and encoding methods have also been proposed for applications including magnetic resonance imaging (MRI) in order to improve acquisition speed or sampling density. These approaches aim to reduce data sampling and mitigate under-sampling artifacts and motion artifacts by combining non-uniform sampling with advanced reconstruction methods.
Therefore, given the above, there is a need for systems and methods for achieving ultra-high resolution imaging in tomographic systems.